Keynote Address

There exist meaningful patterns in test data. Test data analytics, which explores the hidden patterns and correlations in the test data, has a wide range of applications such as reducing test time, improving test quality, identifying outliers for diagnosis, discovering weak links in the manufacturing process, and improving the robustness of the design. There are clear benefits to formulate test problems as data analysis problems and employ existing mathematical tools, as well as develop additional supporting tools, in predictive analytics, data mining, and statistical modeling for uncovering hidden patterns, unknown correlations and other useful information in the production test data. In the talk, we will describe some promising directions in test data analytics and discuss some of their applications.